Machine Generated Data
Tags
Amazon
created on 2023-10-25
Sphere | 91.8 | |
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Aircraft | 91.2 | |
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Helicopter | 91.2 | |
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Transportation | 91.2 | |
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Vehicle | 91.2 | |
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Astronomy | 80.1 | |
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Outer Space | 80.1 | |
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Airplane | 70.3 | |
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Architecture | 57.8 | |
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Building | 57.8 | |
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Wall | 57.8 | |
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Art | 57.3 | |
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Painting | 57.3 | |
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Computer Hardware | 56.9 | |
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Electronics | 56.9 | |
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Hardware | 56.9 | |
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Boat | 56.7 | |
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Sailboat | 56.7 | |
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Hole | 56.3 | |
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Screen | 56.1 | |
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Animal | 55.5 | |
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Invertebrate | 55.5 | |
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Spider | 55.5 | |
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Monitor | 55.4 | |
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Modern Art | 55.3 | |
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Cross | 55.3 | |
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Symbol | 55.3 | |
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Clarifai
created on 2018-10-05
people | 96.4 | |
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image | 96.4 | |
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desktop | 93.2 | |
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symbol | 91.7 | |
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technology | 91.4 | |
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display | 91 | |
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business | 89 | |
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picture frame | 87.9 | |
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retro | 87.9 | |
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moment | 87.2 | |
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illustration | 85.9 | |
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no person | 83.5 | |
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square | 79 | |
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painting | 78.9 | |
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vintage | 78.4 | |
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signalise | 78.1 | |
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graphic | 76.9 | |
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nostalgia | 76.6 | |
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World Wide Web | 76.2 | |
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old | 75.9 | |
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Imagga
created on 2018-10-05
Google
created on 2018-10-05
photograph | 95.4 | |
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black | 95.1 | |
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black and white | 93.1 | |
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photography | 81.8 | |
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monochrome photography | 81 | |
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picture frame | 76 | |
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monochrome | 74.1 | |
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font | 54.9 | |
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product | 53.5 | |
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still life photography | 50.2 | |
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Microsoft
created on 2018-10-05
black | 90.5 | |
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white | 87.6 | |
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old | 42.6 | |
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image | 32.7 | |
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picture frame | 7.6 | |
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Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/44375032/275,229,252,196/full/0/native.jpg)
Helicopter | 91.2% | |
|
![](https://ids.lib.harvard.edu/ids/iiif/44375032/274,226,292,279/full/0/native.jpg)
Airplane | 70.3% | |
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Categories
Imagga
interior objects | 77% | |
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paintings art | 18% | |
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food drinks | 2.1% | |
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text visuals | 1.3% | |
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streetview architecture | 1% | |
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cars vehicles | 0.5% | |
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Captions
Microsoft
created on 2018-10-05
a black and white photo of a sign | 67.5% | |
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a black sign with white letters | 59.2% | |
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a black sign with white text | 59.1% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/44375032/487,34,12,9/full/0/native.jpg)
=
![](https://ids.lib.harvard.edu/ids/iiif/44375032/467,36,11,7/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/44375032/965,34,56,13/full/0/native.jpg)
AGOX
![](https://ids.lib.harvard.edu/ids/iiif/44375032/348,33,70,14/full/0/native.jpg)
KODYK
![](https://ids.lib.harvard.edu/ids/iiif/44375032/433,33,174,13/full/0/native.jpg)
2-7 - = IA kiro
![](https://ids.lib.harvard.edu/ids/iiif/44375032/503,34,32,10/full/0/native.jpg)
IA
![](https://ids.lib.harvard.edu/ids/iiif/44375032/433,33,32,12/full/0/native.jpg)
2-7
![](https://ids.lib.harvard.edu/ids/iiif/44375032/548,34,60,12/full/0/native.jpg)
kiro
![](https://ids.lib.harvard.edu/ids/iiif/44375032/966,33,52,18/full/0/native.jpg)
KODY
![](https://ids.lib.harvard.edu/ids/iiif/44375032/966,33,52,18/full/0/native.jpg)
KODY